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Full catalog/HMA2_LHI
HMA2_LHI·v1·dataset

Daily landslide risk warnings, High Mountain Asia (5 km)

High Mountain Asia Daily 5km Landslide Hazard Indicator V001
atmosphere NASA NSIDC_CPRD Level 4 netCDF-4
In plain English

What it measures. A daily indicator of how likely rainfall-triggered landslides are across High Mountain Asia, at 5-kilometer detail, with projections running from 2015 all the way to 2100 under two different future climate scenarios.

How it's made. Generated by a machine-learning model trained on past temperature, rainfall, and recorded landslides, then fed downscaled climate-model projections to estimate future hazard.

How & where you'd use it. Helps planners and researchers anticipate where and when landslide risk may be high, both today and under different possible climate futures.

What's measured

CLIMATE INDICATORS › LAND SURFACE/AGRICULTURE INDICATORS › LANDSLIDES

Coverage & cadence

  • Time span1990-01-31 → 2019-01-01
  • Measured byMODELS (NOT APPLICABLE)
  • Processing levelLevel 4
  • Spatial extent60, 20, 111, 46
  • FormatsnetCDF-4
  • StatusCOMPLETE

What you can do with it

  • Map air pollutants — NO₂, aerosols, ozone
  • Track greenhouse gases and Earth's energy budget
  • Feed weather and air-quality analysis
Official description

This data set projects the daily hazard of rainfall-triggered landslides in the High Mountain Asia region from 2015 through 2100, at 5 km resolution. Projections are provided for two Shared Socioeconomic Pathways (SSPs)—SSP2-4.5 and SSP5 8.5—based on downscaled temperature and precipitation projections from a 30-member ensemble climate model. Landslide hazard is represented by a landslide hazard indicator (LHI), computed with a machine learning (ML) model trained on historical temperatures and precipitation from 1990 through 2019 and a catalog of documented landslides. Two historical LHI data sets are also available: the ML model LHIs generated for 1990 through 2019; and retrodicted LHIs computed by inputting downscaled temperatures and precipitation for 1990 through 2014 to the ensemble climate model.

Get the data

hma2_lhi_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="HMA2_LHI",
    version="1",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from NSIDC_CPRD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.